Product selection guides are useful, general search tools that allow a user to perform a navigational search. More particularly, a selection guide allows a user to search for a product by iteratively selecting a parameter where each selection causes search results to be reduced by filtering out products whose characteristics do not match the selected parameter(s) while, at the same time, presenting a corresponding reduced set of parameters with which the next search parameter(s) can be selected. Typically, this approach assumes that the customer is searching within an entire line of products, e.g., fasteners or light bulbs, that are stored in a database using a predefined hierarchical structure or taxonomy.
Another common web search paradigm, called direct search, allows users to search for products by entering a list of keywords into the search interface, and the search results will display all products which are associated with one or more of the entered keywords. The two paradigms—navigational search and direct search—can be combined to form a third search paradigm called faceted search. This paradigm allows search along multiple dimensions, with a narrowing of scope along each dimension. This approach has become popular in ecommerce and library applications.
It has been seen, however, that these basic search paradigms by themselves are inefficient because they are not inherently personalized to the user or the user's current purpose or role in an enterprise. As a result, these basic search paradigms make it hard for customers to find what they need as the search results often present products that are irrelevant to the customer. For example, a search query may cause a 50 Hz motor to be provided in a search result when the customer's site is only wired for 60 Hz electricity. Accordingly, a need exists for a search paradigm that takes the customer context into consideration, particularly the physical context, to thereby do a better job of helping customers find what they need.